Underwater surveying and inspection is a significant component of many marine and oceanographic sciences and industries. Considerable costs are incurred in surveying and inspection of artificial structures such as ship hulls; oil and cable pipelines; and oil rigs including associated submerged platforms and risers. There is great demand to improve the efficiency and effectiveness and reduce the costs of these surveys. The growing development of deep sea oil drilling platforms and the necessity to inspect and maintain them is likely to push the demand for inspection services even further. Optical inspection, either by human observation or human analysis of video or photographic data, is required in order to provide the necessary resolution to determine their health and status.
Conventionally the majority of survey and inspection work would have been the preserve of divers but with the increasing demand to access hazardous environments and the continuing requirement by industry to reduce costs, the use of divers is becoming less common and their place being taken by unmanned underwater devices such as Remotely Operated Vehicles (ROV), Autonomous Underwater Vehicles (AUV) and underwater sentries.
ROVs and AUVs are multipurpose platforms and can provide a means to access more remote and hostile environments. They can remain in position for considerable periods while recording and measuring the characteristics of underwater scenes with higher accuracy and repeatability.
An underwater sentry is not mobile and may be fully autonomous or remotely operated. An autonomous sentry may have local power and data storage while a remotely operated unit may have external power and data communications.
Both ROVs and AUVs are typically launched from a ship but while the ROV maintains constant contact with the launch vessel through an umbilical tether, the AUV is independent and may move entirely of its own accord through a pre-programmed route sequence.
The ROV tether houses data, control and power cables and can be piloted from its launch vessel to proceed to locations and commence surveying or inspection duties. The video data typically acquired can be stored locally but is normally transmitted back to the host through a high capacity data link in the tether which is often an optical fibre. For the AV, data is stored locally and only reaches the host after re-docking with the launch ship.
Traditional underwater imaging systems consist of a camera, a means of illumination for lighting purposes and a video system for recording and displaying the scene and to allow storage of the images for future analysis. The illumination means traditionally consist of Halogen lights, HID lights or HMI lights. In an ROV, the lights would be manually controlled by the operator to improve image quality. The cameras typically used have frame rate of 50-60 frames per second (fps).
Video data is recorded and stored in original format for review. Other data such as position, navigation and sonar are also typically recorded and are used to assist these operations. However, optical visibility remains the most important consideration for the efficient conduct of surveying and maintenance operations.
The video stream may be viewed in real time by an operator on board or stored for later review. In some case, data may be transmitted from a survey ship at sea back to another location using a satellite link.
A common use for such ROVs and AUVs is imaging of subsea pipelines and submerged structures associated with oil rigs, for monitoring and maintenance purposes. In such situations, the vehicle will be manoeuvred along the length of the object in question, so as to obtain a complete image thereof.
Transmission of light in water is well characterized and reasonably well understood, in that light at wavelengths corresponding to the blue/green region of the spectrum between 350-550 nm suffers much less absorption, and hence is preferentially transmitted, compared with light in the red region of the section beyond 600 nm. This differing absorption contributes to the resulting blue/green colour that is commonly observed of water.
Traditional underwater imaging is based on the same principles as land based imaging, where video and a white light are used with a colour sensitive, Bayer filtered or 3CCD camera to create a colour image or sequence of images for video. However, it is important to note that Bayer filters reduce the resolution of the captured image, while 3-chip CCD cameras are bulky.
There are a number of specific environmental issues with underwater imaging that have an impact on image quality, for example as mentioned, colour absorption in water. Given typical frame rates of 50 fps, maximum exposure times, which are constrained by the frame rate, of 20 ms are usual. Accordingly, during one frame or image acquisition period it is possible for there to have been relative motion of 20 mm, which can result in blurring, which in turn may have an impact on image quality under certain conditions of object field size, sensor size and magnification.
Particles and backscattered light form floating or moving particles in the field of view are another example of image quality issues in underwater imaging caused by environmental conditions, one that can have a significant impact on the images acquired.
Due to the cost of conducting underwater surveys it is important to maximise the information content of any acquired data and the use of high resolution cameras with sensor sizes of 1920×1080 pixels, compatible with HD TV systems, is increasingly common. Faithful colour capture is a significant concern during any underwater surveying. In order to maintain a high spatial resolution while simultaneously capturing accurate colour information, three chip colour cameras are sometimes used. In such cameras, the incoming light is split into three beams and directed into three separate sensors to capture the red, green and blue components. Maintaining the same spatial resolution requires that each of the red, green and blue sensors must also have a pixel count of 1920×1080. Such a camera captures 5.9 megapixels (Mpx) per frame. Allowing for 1 byte of storage per pixel means that a single frame captured from such a camera would require 5.9 MB of storage. At a progressive scan HD frame rate of 60 Hz, one second of video would require approximately 360 MB and one hour would require 1.25 TB. While conventional image and video compression techniques, such as those used to generate MPEG4 files, are routinely used to reduce the storage and transmission overhead so as to allow about one hour of standard HD video be stored in 2 GB, these techniques may not always be suitable for compressing survey data. Other camera sensors exist that have even higher resolutions and these may be used in some proprietary systems, resulting in even larger volumes of data produced and requiring suitable storage.
It is clear that extensive surveying, at high resolutions, will obviously produce extremely large volumes of data. The storage and transmission of such volumes presents a significant cost to the surveying industry, especially in terms of bandwidth required to transmit the data from offshore locations over satellite communications. In addition to these costs are the labour overheads of the analysis of hours of video data by a human observer who must generally view the video survey in real time.
When performing a survey, determining the dimensions of an object in a survey image can be very important. However, this requires scale information which may be derived from calibration data that has been acquired previously. In such a situation any object within the field of view that is also within the depth of focus of the camera and optical system may have its size estimated by virtue of the known magnification factor associated with the optical system. However, many survey vehicles have optical systems with fixed focus arrangements and/or extensive depths of field which restrict the accuracy that can be reliably achieved when operating over large distances.
The demand for more high quality survey information has promoted the use of range finding techniques in certain applications. These underwater range finding techniques include sonar, LIDAR and time of flight measurements.
Sonar relies on an acoustic signal being generated and then recording the time it takes for a receiver to detect the reflected signal from an object or land mass under survey. More complicated detection schemes based on recording the spread of times over which an acoustic pulse is recorded at the detector allows the sizes of objects to be estimated.
LIDAR works similarly to conventional RADAR, except that laser pulses are used instead of radio waves. A pulsed laser is used to illuminate an object or scene. A detector records the arrival time of pulses reflected from the object or components of the scene. The delay between the transmission and receipt of the reflected pulses allows the range to the objects to be determined according to the formula of Range=c×Time Delay/2, where c is the speed of light in the medium of interest.
The accuracy of this technique is dependent on the resolution of the detection apparatus and has been mainly used for measuring distances on land. Its range underwater is limited to tens of meters due to the high absorption of light in water.
Time of Flight is a variant of LIDAR but is intended to provide much higher resolution through the use of short pulsed or modulated lasers. The timing measurements are, in general, more sophisticated to enable times as short as a few picoseconds to be determined which in turn allows spatial resolutions down to 1 mm to be achieved.
These scaling and ranging techniques all require specialised and complicated technology. They are expensive to develop, generally bulky and difficult to maintain. Furthermore, for underwater use, they require enhancements in processing for signal to noise improvements when compared to in air operation.